Polygons#

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import hvplot.pandas  # noqa

Using hvplot with geopandas is as simple as loading a geopandas dataframe and calling hvplot on it with geo=True.

import geopandas as gpd

countries = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
countries.sample(5)
pop_est continent name iso_a3 gdp_md_est geometry
171 2103721 Europe Macedonia MKD 29520.0 POLYGON ((22.38053 42.32026, 22.88137 41.99930...
150 1972126 Europe Slovenia SVN 68350.0 POLYGON ((13.80648 46.50931, 14.63247 46.43182...
68 1772255 Africa Gabon GAB 35980.0 POLYGON ((11.27645 2.26105, 11.75167 2.32676, ...
36 9038741 North America Honduras HND 43190.0 POLYGON ((-83.14722 14.99583, -83.48999 15.016...
64 6163195 Africa Sierra Leone SLE 10640.0 POLYGON ((-13.24655 8.90305, -12.71196 9.34271...
countries.hvplot(geo=True)

Control the color of the elements using the c option.

countries.hvplot.polygons(geo=True, c='pop_est', hover_cols='all')

You can even color by another series, such as population density:

countries.hvplot.polygons(geo=True, c=countries.pop_est/countries.area, clabel='pop density')
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Download this notebook from GitHub (right-click to download).